Deep-PK: deep learning for small molecule pharmacokinetic and toxicity prediction
Baker Heart and Diabetes Institute · The University of Queensland · +1 more institution
Abstract
Evaluating pharmacokinetic properties of small molecules is considered a key feature in most drug development and high-throughput screening processes. Generally, pharmacokinetics, which represent the fate of drugs in the human body, are described from four perspectives: absorption, distribution, metabolism and excretion-all of which are closely related to a fifth perspective, toxicity (ADMET). Since obtaining ADMET data from in vitro, in vivo or pre-clinical stages is time consuming and expensive, many efforts have been made to predict ADMET properties via computational approaches. However, the majority of available methods are limited in their ability to provide pharmacokinetics and toxicity for diverse…
Citation impact
- FWCI
- 80.11
- Percentile
- 100%
- References
- 47
Authors
3- YMYoochan MyungCorresponding
Baker Heart and Diabetes Institute, The University of Queensland
- AGAlex G. C. de Sá
Baker Heart and Diabetes Institute, The University of Queensland, The University of Melbourne
- DBDavid B. Ascher
Baker Heart and Diabetes Institute, The University of Queensland, The University of Melbourne
Topics & keywords
- Interpretability
- Pharmacokinetics
- Deep learning
- Drug discovery
- ADME
- Computational biology
- Computer science
- Small molecule